Breast Cancer Consensus Subtypes: A system for subtyping breast cancer tumors based on gene expression.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34642313", "kind": "science-record", "revision": 4, "content_hash": "sha256:2e1969006f5dad9571aeb61d194bd41523ffd957fd0415c1cfdac15a90bb0561", "created_at": "2026-11-01T17:36:17Z", "updated_at": "2026-11-01T22:04:56Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Breast Cancer Consensus Subtypes: A system for subtyping breast cancer tumors based on gene expression.", "doi": "10.1038/s41523-021-00345-2", "pmid": "34642313", "authors": ["Christina Horr", "Steven A Buechler"], "journal": "NPJ breast cancer", "year": 2021, "abstract": "Breast cancer is heterogeneous in prognoses and drug responses. To organize breast cancers by gene expression independent of statistical methodology, we identified the Breast Cancer Consensus Subtypes (BCCS) as the consensus groupings of six different subtyping methods. Our classification software identified seven BCCS subtypes in a study cohort of publicly available data (n = 5950) including METABRIC, TCGA-BRCA, and data assayed by Affymetrix arrays. All samples were fresh-frozen from primary tumors. The estrogen receptor-positive (ER+) BCCS subtypes were: PCS1 (18%) good prognosis, stromal infiltration; PCS2 (15%) poor prognosis, highly proliferative; PCS3 (13%) poor prognosis, highly proliferative, activated IFN-gamma signaling, cytotoxic lymphocyte infiltration, high tumor mutation burden; PCS4 (18%) good prognosis, hormone response genes highly expressed. The ER- BCCS subtypes were: NCS1 (11%) basal; NCS2 (10%) elevated androgen response; NCS3 (5%) cytotoxic lymphocyte infiltration; unclassified tumors (9%). HER2+ tumors were heterogeneous with respect to BCCS.", "claims": [{"id": "claim-method", "statement": "The consensus subtyping method, as it was applied to create the CMS of colorectal cancer9, consists of the steps: (1) creating multiple subtyping systems using a variety of methods, (2) clustering the network of all possible subtypes, (3) for each clustered set of subtypes, identifying samples frequently assigned to the cluster’s subtypes, so-called core samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34642313", "locator": "sections[19] \"Consensus subtyping method\" paragraph 2", "quote": "The consensus subtyping method, as it was applied to create the CMS of colorectal cancer9, consists of the steps: (1) creating multiple subtyping systems using a variety of methods, (2) clustering the network of all possible subtypes, (3) for each clustered set of subtypes, identifying samples frequently assigned to the cluster’s subtypes, so-called core samples."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Our classification software identified seven BCCS subtypes in a study cohort of publicly available data (n = 5950) including METABRIC, TCGA-BRCA, and data assayed by Affymetrix arrays.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34642313", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Our classification software identified seven BCCS subtypes in a study cohort of publicly available data (n = 5950) including METABRIC, TCGA-BRCA, and data assayed by Affymetrix arrays."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Our classification software identified seven BCCS subtypes in a study cohort of publicly available data (n = 5950) including METABRIC, TCGA-BRCA, and data assayed by Affymetrix arrays.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:34642313"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:accession_absent"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34642313", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1038/s41523-021-00345-2", "sha256": "sha256:d793be56c13d755fd735fe9dd77de75121193b4029dbd865031bafab543c6199", "bytes": 58482, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1038/s41523-021-00345-2", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8511026", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}], "gaps": []}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "correlation_analysis", "specific": "pearson", "label": "Correlation analysis", "dsl_operations": ["pearson_r"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 0.8, "band": "high", "quote": "Pearson correlation"}}, {"id": "method-2", "family": "clustering", "specific": "kmeans", "label": "Clustering", "dsl_operations": ["kmeans_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["feature_matrix"], "evidence": {"score": 0.8, "band": "high", "quote": "k-means"}}, {"id": "method-3", "family": "clustering", "specific": "hierarchical", "label": "Clustering", "dsl_operations": ["hierarchical_cluster"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["feature_matrix"], "evidence": {"score": 0.8, "band": "high", "quote": "hierarchical clustering"}}, {"id": "method-4", "family": "diagnostic_evaluation", "specific": "roc", "label": "Diagnostic test evaluation", "dsl_operations": ["confusion_counts", "roc_curve", "sensitivity_specificity", "solve_confusion_matrix", "classification_metrics", "published_precision_envelope"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["reference_standard_and_test"], "evidence": {"score": 0.8, "band": "high", "quote": "ROC curve"}}, {"id": "method-5", "family": null, "specific": null, "label": "consensus subtyping method", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The consensus subtyping method, as it was applied to create the CMS of colorectal cancer9, consists of the steps: (1) creating multiple subtyping systems using a variety of methods, (2) clustering the network of all possible subtypes, (3) for each clustered set of subtypes, identifying samples frequently assigned to the cluster’s subtypes, so-called core samples."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "blocked", "tier": "R4", "blocking_axis": "data", "blocked_on": "data:accession_absent", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["pearson_r"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: pearson."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R4", "reachable": false, "accessions": [], "resolved_accessions": [], "statements": [], "basis": "The paper names no accession to its source data, so the data has to come from the authors."}}, "can_run": {"dsl_operations": ["pearson_r"], "assets": ["source:pmid:34642313"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:None"]}, "gaps": ["data:accession_absent"]}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T17:04:14Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 5, "usage": {"prompt_tokens": 15967, "completion_tokens": 5753, "cached_tokens": 188}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:34642313", "type": "paper", "label": "pmid:34642313"}, {"id": "source:pmid:34642313", "type": "manuscript", "label": "PMID 34642313 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:34642313", "type": "paper", "label": "pmid:34642313"}, {"id": "source:pmid:34642313", "type": "manuscript", "label": "PMID 34642313 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-34642313", "type": "extraction", "used": ["source:pmid:34642313"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-None", "type": "accession_resolution", "used": ["data:geo:None"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:34642313", "parent_hash": "sha256:85f968fd2b8246d3c88554b1a7eb0a854b8d0c196525eebe1edcee74ebf3210d", "fork_of": null, "generation": 3}, "gaps": ["execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique", "step:obtain_source_data blocked on data:accession_absent"], "assays": [{"role": "data_generation", "definition_id": "apoptosis_assay", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.69, "evidence": ["sponse, IL6-JAK-STAT3 signaling, complement, apoptosis, P53 pathway, and other pathways related to"], "order_basis": "paper_text_order:3118", "id": "assay:1"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["re more likely to be <90% positive for ER by immunohistochemistry (p = 2.1 × 10−8), PCS4 samples were more lik"], "order_basis": "paper_text_order:5701", "id": "assay:2"}, {"role": "analysis", "definition_id": "correlation_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["pearson_r"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.8, "evidence": ["Pearson correlation"], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}